Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Marathi
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use var2093/whisper-tiny-mr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use var2093/whisper-tiny-mr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="var2093/whisper-tiny-mr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("var2093/whisper-tiny-mr") model = AutoModelForSpeechSeq2Seq.from_pretrained("var2093/whisper-tiny-mr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from var2093/whisper-tiny-mr: direct link, hf CLI and curl.
- Browser
- Download file 3.71 kB
-
https://huggingface.co/var2093/whisper-tiny-mr/resolve/main/training_args.bin
- Command line
-
hf download hf://var2093/whisper-tiny-mr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/var2093/whisper-tiny-mr/resolve/main/training_args.bin
3.71 kB
- Xet hash:
- 0805c34c049a596337be3da713bbebdf2cdb92c34a4da5217864ca8483135e5f
- Size of remote file:
- 3.71 kB
- SHA256:
- 417328f736ff25bc229d0420427679a8602e988edccb6a25499d3a4160df65b3
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